Both Descartes and Orbital are playing in the emerging market of geospatial analytics. These companies use machine learning to produce insights from satellite imagery and other data. This capability has proved exceedingly popular with hedge funds where images of store parking lots, for example, can be used to project out revenue numbers. But companies running the gamut from agriculture to logistics see the value in having an extra pair of trained eyes in the sky.

Most of Descartes previous investors participated in today’s growth round. Crosslink Capital and Cultivian Sandbox participated though Data Collective did not. The company previously raised $8.3 million in funding.

Right out of the gate, one of the more unique things about Descartes is that it is headquartered in Santa Fe, New Mexico. Co-founder Mark Johnson pitched Santa Fe to me as a place where an engineer and his or her family can actually buy a house. Today’s raise is one of the largest in the history of New Mexico.

“Our original founding thesis was that lots of money was going to satellite hardware but not to the equivalent software,” Johnson explained to me in an interview.

In the three years since, more money than ever has been spent on geospatial software technologies. Johnson noted the number of startups he meets on a weekly basis trying to do interesting things combining deep learning and the myriad of images taken from different satellites every day continues to grow.

As Descartes’ internal data pipelines have been getting more and more robust, talk has slowly shifted to opening up the platform to a wider audience. Everyone in the space knows that the real money will be made through massive SaaS contracts and not through one-off consulting contracts.

The hope is that Descartes can open up all of its technology in an easy to use way such that customers can search across the globe. Geovisual Search was an initial crack at this — implementing computer vision to quantify physical infrastructure. With this tool, you can search for wastewater treatment plants or cargo ships and automatically count and identify them.

The biggest challenge is getting companies into a position where they can get the most out of using Descartes’ platform. Extracting data, cleaning it and thinking about data science methodologies isn’t always the easiest thing to do. This is the main reason that Descartes is prioritizing accessibility.

Today the startup has 40 employees. Johnson is looking to grow the team to around 50 or 60 by the end of the year and 100 next year. Much of this hiring will happen in product and sales. The team is toying with the idea of increasing the number of verticalized offerings — in the near future you could hypothetically see a dedicated platform for agriculture with built-in land use classifications.